{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Causal discovery with `TIGRAMITE`\n",
    "\n",
    "TIGRAMITE is a time series analysis python module. It allows to reconstruct graphical models (conditional independence graphs) from discrete or continuously-valued time series based on the PCMCI framework and create high-quality plots of the results.\n",
    "\n",
    "PCMCI is described here:\n",
    "J. Runge, P. Nowack, M. Kretschmer, S. Flaxman, D. Sejdinovic, \n",
    "Detecting and quantifying causal associations in large nonlinear time series datasets. Sci. Adv. 5, eaau4996 (2019) \n",
    "https://advances.sciencemag.org/content/5/11/eaau4996\n",
    "\n",
    "For further versions of PCMCI (e.g., PCMCI+, LPCMCI, etc.), see the corresponding tutorials.\n",
    "\n",
    "This tutorial explains the missing values and masking and gives walk-through examples. See the following paper for theoretical background:\n",
    "Runge, Jakob. 2018. “Causal Network Reconstruction from Time Series: From Theoretical Assumptions to Practical Estimation.” Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (7): 075310.\n",
    "\n",
    "Last, the following Nature Communications Perspective paper provides an overview of causal inference methods in general, identifies promising applications, and discusses methodological challenges (exemplified in Earth system sciences): \n",
    "https://www.nature.com/articles/s41467-019-10105-3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imports\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline     \n",
    "## use `%matplotlib notebook` for interactive figures\n",
    "# plt.style.use('ggplot')\n",
    "import sklearn\n",
    "\n",
    "import tigramite\n",
    "from tigramite import data_processing as pp\n",
    "from tigramite.toymodels import structural_causal_processes as toys\n",
    "from tigramite import plotting as tp\n",
    "from tigramite.pcmci import PCMCI\n",
    "\n",
    "from tigramite.independence_tests.parcorr import ParCorr\n",
    "from tigramite.independence_tests.gpdc import GPDC\n",
    "from tigramite.independence_tests.cmiknn import CMIknn\n",
    "from tigramite.independence_tests.cmisymb import CMIsymb\n",
    "\n",
    "from tigramite.models import LinearMediation, Prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing values\n",
    "\n",
    "Tigramite consistently handles missing values. For example, missing values denoted as ``999.`` in the data can be flagged with ``DataFrame(..., missing_flag=999.)``. Then all time slices of samples where missing values occur in any variable are dismissed while consistently handling time lags. \n",
    "\n",
    "__Note:__ Prior to version 5 the DataFrame had the default setting to dismiss subsequent samples for all lags up to ``2*tau_max``. This was intended to avoid biases. But since this only leads to biases for data where missing values occur non-randomly, this setting is overly conservative and leads to too many samples being dismissed. Hence, since version 5 there is another parameter for initializing the DataFrame and ``remove_missing_upto_maxlag=False`` is the default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(1)\n",
    "data = np.random.randn(100, 3)\n",
    "for t in range(1, 100):\n",
    "    data[t, 0] += 0.7*data[t-1, 0] \n",
    "    data[t, 1] += 0.8*data[t-1, 1] + 0.8*data[t-1,0]\n",
    "    data[t, 2] += 0.8*data[t-1, 2] + 0.8*data[t-1,1]\n",
    "# Randomly mark 10% of values as missing values in variable 2\n",
    "data[np.random.permutation(100)[:10], 2] = 999.\n",
    "\n",
    "# Initialize dataframe object, specify time axis and variable names\n",
    "var_names = [r'$X^0$', r'$X^1$', r'$X^2$']\n",
    "dataframe = pp.DataFrame(data, \n",
    "                         datatime = np.arange(len(data)), \n",
    "                         var_names=var_names,\n",
    "                         missing_flag=999.)\n",
    "\n",
    "tp.plot_timeseries(dataframe); plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "# Initialize conditional independence test\n",
      "\n",
      "Parameters:\n",
      "independence test = par_corr\n",
      "significance = analytic\n",
      "\n",
      "##\n",
      "## Step 1: PC1 algorithm for selecting lagged conditions\n",
      "##\n",
      "\n",
      "Parameters:\n",
      "independence test = par_corr\n",
      "tau_min = 1\n",
      "tau_max = 2\n",
      "pc_alpha = [0.2]\n",
      "max_conds_dim = None\n",
      "max_combinations = 1\n",
      "\n",
      "\n",
      "\n",
      "## Variable $X^0$\n",
      "\n",
      "Iterating through pc_alpha = [0.2]:\n",
      "\n",
      "# pc_alpha = 0.2 (1/1):\n",
      "\n",
      "Testing condition sets of dimension 0:\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^0$ (1/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.688 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.688\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^0$ (2/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.449 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.449\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^0$ (3/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.355 | pval = 0.00039 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00039 / val =  0.355\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^0$ (4/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.248 | pval = 0.01470 | dependent = True \n",
      "    Subset 0: () gives pval = 0.01470 / val =  0.248\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^0$ (5/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.152 | pval = 0.16123 | dependent = True \n",
      "    Subset 0: () gives pval = 0.16123 / val =  0.152\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^2$ -2) -?> $X^0$ (6/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.129 | pval = 0.23578 | dependent = False \n",
      "    Subset 0: () gives pval = 0.23578 / val =  0.129\n",
      "    Non-significance detected.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^0$ has 5 link(s):\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.688\n",
      "        ($X^0$ -2): max_pval = 0.00000, |min_val| =  0.449\n",
      "        ($X^1$ -1): max_pval = 0.00039, |min_val| =  0.355\n",
      "        ($X^1$ -2): max_pval = 0.01470, |min_val| =  0.248\n",
      "        ($X^2$ -1): max_pval = 0.16123, |min_val| =  0.152\n",
      "\n",
      "Testing condition sets of dimension 1:\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^0$ (1/5):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.585 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^0$ -2)  gives pval = 0.00000 / val =  0.585\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^0$ (2/5):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.052 | pval = 0.61676 | dependent = False \n",
      "    Subset 0: ($X^0$ -1)  gives pval = 0.61676 / val = -0.052\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^0$ (3/5):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.018 | pval = 0.86238 | dependent = False \n",
      "    Subset 0: ($X^0$ -1)  gives pval = 0.86238 / val =  0.018\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^0$ (4/5):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.006 | pval = 0.95598 | dependent = False \n",
      "    Subset 0: ($X^0$ -1)  gives pval = 0.95598 / val =  0.006\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^0$ (5/5):\n",
      "            Constructed array of shape (3, 86) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.001 | pval = 0.99188 | dependent = False \n",
      "    Subset 0: ($X^0$ -1)  gives pval = 0.99188 / val = -0.001\n",
      "    Non-significance detected.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^0$ has 1 link(s):\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.585\n",
      "\n",
      "Algorithm converged for variable $X^0$\n",
      "\n",
      "## Variable $X^1$\n",
      "\n",
      "Iterating through pc_alpha = [0.2]:\n",
      "\n",
      "# pc_alpha = 0.2 (1/1):\n",
      "\n",
      "Testing condition sets of dimension 0:\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^1$ (1/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.725 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.725\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^1$ (2/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.790 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.790\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^1$ (3/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.903 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.903\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^1$ (4/6):\n",
      "            Constructed array of shape (2, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.776 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.776\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^1$ (5/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.534 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.534\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^2$ -2) -?> $X^1$ (6/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.431 | pval = 0.00003 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00003 / val =  0.431\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^1$ has 6 link(s):\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.903\n",
      "        ($X^0$ -2): max_pval = 0.00000, |min_val| =  0.790\n",
      "        ($X^1$ -2): max_pval = 0.00000, |min_val| =  0.776\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.725\n",
      "        ($X^2$ -1): max_pval = 0.00000, |min_val| =  0.534\n",
      "        ($X^2$ -2): max_pval = 0.00003, |min_val| =  0.431\n",
      "\n",
      "Testing condition sets of dimension 1:\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^1$ (1/6):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.780 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^0$ -2)  gives pval = 0.00000 / val =  0.780\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^1$ (2/6):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.451 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^1$ -1)  gives pval = 0.00000 / val =  0.451\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^1$ (3/6):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.191 | pval = 0.06359 | dependent = True \n",
      "    Subset 0: ($X^1$ -1)  gives pval = 0.06359 / val = -0.191\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^1$ (4/6):\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.736 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^1$ -1)  gives pval = 0.00000 / val =  0.736\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^1$ (5/6):\n",
      "            Constructed array of shape (3, 86) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.181 | pval = 0.09800 | dependent = True \n",
      "    Subset 0: ($X^1$ -1)  gives pval = 0.09800 / val = -0.181\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^2$ -2) -?> $X^1$ (6/6):\n",
      "            Constructed array of shape (3, 86) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.113 | pval = 0.30104 | dependent = False \n",
      "    Subset 0: ($X^1$ -1)  gives pval = 0.30104 / val = -0.113\n",
      "    Non-significance detected.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^1$ has 5 link(s):\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.780\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.725\n",
      "        ($X^0$ -2): max_pval = 0.00000, |min_val| =  0.451\n",
      "        ($X^1$ -2): max_pval = 0.06359, |min_val| =  0.191\n",
      "        ($X^2$ -1): max_pval = 0.09800, |min_val| =  0.181\n",
      "\n",
      "Testing condition sets of dimension 2:\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^1$ (1/5):\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(0, -1), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.856 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^0$ -1) ($X^0$ -2)  gives pval = 0.00000 / val =  0.856\n",
      "    Still subsets of dimension 2 left, but q_max = 1 reached.\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^1$ (2/5):\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.654 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^1$ -1) ($X^0$ -2)  gives pval = 0.00000 / val =  0.654\n",
      "    Still subsets of dimension 2 left, but q_max = 1 reached.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^1$ (3/5):\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.078 | pval = 0.45596 | dependent = False \n",
      "    Subset 0: ($X^1$ -1) ($X^0$ -1)  gives pval = 0.45596 / val =  0.078\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^1$ (4/5):\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.013 | pval = 0.90014 | dependent = False \n",
      "    Subset 0: ($X^1$ -1) ($X^0$ -1)  gives pval = 0.90014 / val = -0.013\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^1$ (5/5):\n",
      "            Constructed array of shape (4, 86) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.051 | pval = 0.64715 | dependent = False \n",
      "    Subset 0: ($X^1$ -1) ($X^0$ -1)  gives pval = 0.64715 / val = -0.051\n",
      "    Non-significance detected.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^1$ has 2 link(s):\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.780\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.654\n",
      "\n",
      "Algorithm converged for variable $X^1$\n",
      "\n",
      "## Variable $X^2$\n",
      "\n",
      "Iterating through pc_alpha = [0.2]:\n",
      "\n",
      "# pc_alpha = 0.2 (1/1):\n",
      "\n",
      "Testing condition sets of dimension 0:\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^2$ (1/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.277 | pval = 0.00994 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00994 / val =  0.277\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^2$ (2/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.401 | pval = 0.00013 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00013 / val =  0.401\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^2$ (3/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.782 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.782\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^2$ (4/6):\n",
      "            Constructed array of shape (2, 86) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.864 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.864\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^2$ (5/6):\n",
      "            Constructed array of shape (2, 77) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.979 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.979\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Link ($X^2$ -2) -?> $X^2$ (6/6):\n",
      "            Constructed array of shape (2, 77) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = []\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.936 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: () gives pval = 0.00000 / val =  0.936\n",
      "    No conditions of dimension 0 left.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^2$ has 6 link(s):\n",
      "        ($X^2$ -1): max_pval = 0.00000, |min_val| =  0.979\n",
      "        ($X^2$ -2): max_pval = 0.00000, |min_val| =  0.936\n",
      "        ($X^1$ -2): max_pval = 0.00000, |min_val| =  0.864\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.782\n",
      "        ($X^0$ -2): max_pval = 0.00013, |min_val| =  0.401\n",
      "        ($X^0$ -1): max_pval = 0.00994, |min_val| =  0.277\n",
      "\n",
      "Testing condition sets of dimension 1:\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^2$ (1/6):\n",
      "            Constructed array of shape (3, 69) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.872 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^2$ -2)  gives pval = 0.00000 / val =  0.872\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^2$ -2) -?> $X^2$ (2/6):\n",
      "            Constructed array of shape (3, 69) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.538 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^2$ -1)  gives pval = 0.00000 / val = -0.538\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^2$ (3/6):\n",
      "            Constructed array of shape (3, 77) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.746 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^2$ -1)  gives pval = 0.00000 / val =  0.746\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^2$ (4/6):\n",
      "            Constructed array of shape (3, 77) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.915 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^2$ -1)  gives pval = 0.00000 / val =  0.915\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^2$ (5/6):\n",
      "            Constructed array of shape (3, 77) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.707 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^2$ -1)  gives pval = 0.00000 / val =  0.707\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^2$ (6/6):\n",
      "            Constructed array of shape (3, 77) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.461 | pval = 0.00003 | dependent = True \n",
      "    Subset 0: ($X^2$ -1)  gives pval = 0.00003 / val =  0.461\n",
      "    No conditions of dimension 1 left.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^2$ has 6 link(s):\n",
      "        ($X^2$ -1): max_pval = 0.00000, |min_val| =  0.872\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.782\n",
      "        ($X^1$ -2): max_pval = 0.00000, |min_val| =  0.746\n",
      "        ($X^2$ -2): max_pval = 0.00000, |min_val| =  0.538\n",
      "        ($X^0$ -2): max_pval = 0.00013, |min_val| =  0.401\n",
      "        ($X^0$ -1): max_pval = 0.00994, |min_val| =  0.277\n",
      "\n",
      "Testing condition sets of dimension 2:\n",
      "\n",
      "    Link ($X^2$ -1) -?> $X^2$ (1/6):\n",
      "            Constructed array of shape (4, 77) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(1, -1), (1, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.986 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^1$ -1) ($X^1$ -2)  gives pval = 0.00000 / val =  0.986\n",
      "    Still subsets of dimension 2 left, but q_max = 1 reached.\n",
      "\n",
      "    Link ($X^1$ -1) -?> $X^2$ (2/6):\n",
      "            Constructed array of shape (4, 77) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.795 | pval = 0.00000 | dependent = True \n",
      "    Subset 0: ($X^2$ -1) ($X^1$ -2)  gives pval = 0.00000 / val =  0.795\n",
      "    Still subsets of dimension 2 left, but q_max = 1 reached.\n",
      "\n",
      "    Link ($X^1$ -2) -?> $X^2$ (3/6):\n",
      "            Constructed array of shape (4, 77) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.015 | pval = 0.90125 | dependent = False \n",
      "    Subset 0: ($X^2$ -1) ($X^1$ -1)  gives pval = 0.90125 / val =  0.015\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^2$ -2) -?> $X^2$ (4/6):\n",
      "            Constructed array of shape (4, 69) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.342 | pval = 0.00463 | dependent = True \n",
      "    Subset 0: ($X^2$ -1) ($X^1$ -1)  gives pval = 0.00463 / val =  0.342\n",
      "    Still subsets of dimension 2 left, but q_max = 1 reached.\n",
      "\n",
      "    Link ($X^0$ -2) -?> $X^2$ (5/6):\n",
      "            Constructed array of shape (4, 77) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.013 | pval = 0.91292 | dependent = False \n",
      "    Subset 0: ($X^2$ -1) ($X^1$ -1)  gives pval = 0.91292 / val = -0.013\n",
      "    Non-significance detected.\n",
      "\n",
      "    Link ($X^0$ -1) -?> $X^2$ (6/6):\n",
      "            Constructed array of shape (4, 77) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.150 | pval = 0.20014 | dependent = False \n",
      "    Subset 0: ($X^2$ -1) ($X^1$ -1)  gives pval = 0.20014 / val = -0.150\n",
      "    Non-significance detected.\n",
      "\n",
      "    Sorting parents in decreasing order with \n",
      "    weight(i-tau->j) = min_{iterations} |val_{ij}(tau)| \n",
      "\n",
      "Updating parents:\n",
      "\n",
      "    Variable $X^2$ has 3 link(s):\n",
      "        ($X^2$ -1): max_pval = 0.00000, |min_val| =  0.872\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.782\n",
      "        ($X^2$ -2): max_pval = 0.00463, |min_val| =  0.342\n",
      "\n",
      "Algorithm converged for variable $X^2$\n",
      "\n",
      "## Resulting lagged parent (super)sets:\n",
      "\n",
      "    Variable $X^0$ has 1 link(s):\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.585\n",
      "\n",
      "    Variable $X^1$ has 2 link(s):\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.780\n",
      "        ($X^0$ -1): max_pval = 0.00000, |min_val| =  0.654\n",
      "\n",
      "    Variable $X^2$ has 3 link(s):\n",
      "        ($X^2$ -1): max_pval = 0.00000, |min_val| =  0.872\n",
      "        ($X^1$ -1): max_pval = 0.00000, |min_val| =  0.782\n",
      "        ($X^2$ -2): max_pval = 0.00463, |min_val| =  0.342\n",
      "\n",
      "##\n",
      "## Step 2: MCI algorithm\n",
      "##\n",
      "\n",
      "Parameters:\n",
      "\n",
      "independence test = par_corr\n",
      "tau_min = 0\n",
      "tau_max = 2\n",
      "max_conds_py = None\n",
      "max_conds_px = None\n",
      "\n",
      "        link ($X^0$ -1) -?> $X^0$ (1/8):\n",
      "        with conds_y = [ ]\n",
      "        with conds_x = [ ($X^0$ -2) ]\n",
      "            Constructed array of shape (3, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.585 | pval = 0.00000 | dependent = True [cached]\n",
      "\n",
      "        link ($X^0$ -2) -?> $X^0$ (2/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^0$ -3) ]\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (0, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.048 | pval = 0.64516 | dependent = False \n",
      "\n",
      "        link ($X^1$  0) o?o $X^0$ (3/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(1, 0)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (1, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.072 | pval = 0.48950 | dependent = False \n",
      "\n",
      "        link ($X^1$ -1) -?> $X^0$ (4/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^1$ -2) ($X^0$ -2) ]\n",
      "            Constructed array of shape (5, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (1, -2), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.091 | pval = 0.38447 | dependent = False \n",
      "\n",
      "        link ($X^1$ -2) -?> $X^0$ (5/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^1$ -3) ($X^0$ -3) ]\n",
      "            Constructed array of shape (5, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (1, -3), (0, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.048 | pval = 0.64957 | dependent = False \n",
      "\n",
      "        link ($X^2$  0) o?o $X^0$ (6/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(2, 0)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (2, -1), (1, -1), (2, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.068 | pval = 0.59118 | dependent = False \n",
      "\n",
      "        link ($X^2$ -1) -?> $X^0$ (7/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -2) ($X^1$ -2) ($X^2$ -3) ]\n",
      "            Constructed array of shape (6, 70) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (2, -2), (1, -2), (2, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.118 | pval = 0.34583 | dependent = False \n",
      "\n",
      "        link ($X^2$ -2) -?> $X^0$ (8/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -3) ($X^1$ -3) ($X^2$ -4) ]\n",
      "            Constructed array of shape (6, 71) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(0, 0)]\n",
      "            Z = [(0, -1), (2, -3), (1, -3), (2, -4)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.007 | pval = 0.95741 | dependent = False \n",
      "\n",
      "        link ($X^0$  0) o?o $X^1$ (1/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^0$ -1) ]\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(0, 0)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.072 | pval = 0.48950 | dependent = False [cached]\n",
      "\n",
      "        link ($X^0$ -1) -?> $X^1$ (2/8):\n",
      "        with conds_y = [ ($X^1$ -1) ]\n",
      "        with conds_x = [ ($X^0$ -2) ]\n",
      "            Constructed array of shape (4, 96) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.654 | pval = 0.00000 | dependent = True [cached]\n",
      "\n",
      "        link ($X^0$ -2) -?> $X^1$ (3/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^0$ -3) ]\n",
      "            Constructed array of shape (5, 96) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1), (0, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.098 | pval = 0.34941 | dependent = False \n",
      "\n",
      "        link ($X^1$ -1) -?> $X^1$ (4/8):\n",
      "        with conds_y = [ ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^1$ -2) ($X^0$ -2) ]\n",
      "            Constructed array of shape (5, 96) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(0, -1), (1, -2), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.560 | pval = 0.00000 | dependent = True \n",
      "\n",
      "        link ($X^1$ -2) -?> $X^1$ (5/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^1$ -3) ($X^0$ -3) ]\n",
      "            Constructed array of shape (6, 96) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1), (1, -3), (0, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.151 | pval = 0.15061 | dependent = False \n",
      "\n",
      "        link ($X^2$  0) o?o $X^1$ (6/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(2, 0)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1), (2, -1), (2, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.057 | pval = 0.65168 | dependent = False \n",
      "\n",
      "        link ($X^2$ -1) -?> $X^1$ (7/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -2) ($X^1$ -2) ($X^2$ -3) ]\n",
      "            Constructed array of shape (7, 70) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1), (2, -2), (1, -2), (2, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.250 | pval = 0.04498 | dependent = False \n",
      "\n",
      "        link ($X^2$ -2) -?> $X^1$ (8/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -3) ($X^1$ -3) ($X^2$ -4) ]\n",
      "            Constructed array of shape (7, 71) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(1, 0)]\n",
      "            Z = [(1, -1), (0, -1), (2, -3), (1, -3), (2, -4)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.057 | pval = 0.64695 | dependent = False \n",
      "\n",
      "        link ($X^0$  0) o?o $X^2$ (1/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^0$ -1) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(0, 0)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1), (2, -2), (0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.068 | pval = 0.59118 | dependent = False [cached]\n",
      "\n",
      "        link ($X^0$ -1) -?> $X^2$ (2/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^0$ -2) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(0, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1), (2, -2), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.135 | pval = 0.28206 | dependent = False \n",
      "\n",
      "        link ($X^0$ -2) -?> $X^2$ (3/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^0$ -3) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(0, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1), (2, -2), (0, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val = -0.188 | pval = 0.13451 | dependent = False \n",
      "\n",
      "        link ($X^1$  0) o?o $X^2$ (4/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^1$ -1) ($X^0$ -1) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(1, 0)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1), (2, -2), (0, -1)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.057 | pval = 0.65168 | dependent = False [cached]\n",
      "\n",
      "        link ($X^1$ -1) -?> $X^2$ (5/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^1$ -2) ($X^0$ -2) ]\n",
      "            Constructed array of shape (6, 69) from\n",
      "            X = [(1, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (2, -2), (1, -2), (0, -2)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.731 | pval = 0.00000 | dependent = True \n",
      "\n",
      "        link ($X^1$ -2) -?> $X^2$ (6/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^1$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^1$ -3) ($X^0$ -3) ]\n",
      "            Constructed array of shape (7, 69) from\n",
      "            X = [(1, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1), (2, -2), (1, -3), (0, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.152 | pval = 0.23139 | dependent = False \n",
      "\n",
      "        link ($X^2$ -1) -?> $X^2$ (7/8):\n",
      "        with conds_y = [ ($X^1$ -1) ($X^2$ -2) ]\n",
      "        with conds_x = [ ($X^2$ -2) ($X^1$ -2) ($X^2$ -3) ]\n",
      "            Constructed array of shape (6, 63) from\n",
      "            X = [(2, -1)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(1, -1), (2, -2), (1, -2), (2, -3)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.415 | pval = 0.00108 | dependent = True \n",
      "\n",
      "        link ($X^2$ -2) -?> $X^2$ (8/8):\n",
      "        with conds_y = [ ($X^2$ -1) ($X^1$ -1) ]\n",
      "        with conds_x = [ ($X^2$ -3) ($X^1$ -3) ($X^2$ -4) ]\n",
      "            Constructed array of shape (7, 58) from\n",
      "            X = [(2, -2)]\n",
      "            Y = [(2, 0)]\n",
      "            Z = [(2, -1), (1, -1), (2, -3), (1, -3), (2, -4)]\n",
      "            extraZ = []\n",
      "            with missing values = 999.0 removed\n",
      "        val =  0.238 | pval = 0.08553 | dependent = False \n",
      "\n",
      "## Significant links at alpha = 0.01:\n",
      "\n",
      "    Variable $X^0$ has 1 link(s):\n",
      "        ($X^0$ -1): pval = 0.00000 | val =  0.585\n",
      "\n",
      "    Variable $X^1$ has 2 link(s):\n",
      "        ($X^0$ -1): pval = 0.00000 | val =  0.654\n",
      "        ($X^1$ -1): pval = 0.00000 | val =  0.560\n",
      "\n",
      "    Variable $X^2$ has 2 link(s):\n",
      "        ($X^1$ -1): pval = 0.00000 | val =  0.731\n",
      "        ($X^2$ -1): pval = 0.00108 | val =  0.415\n"
     ]
    }
   ],
   "source": [
    "pcmci_parcorr = PCMCI(dataframe=dataframe, cond_ind_test=ParCorr(verbosity=3), verbosity=4)\n",
    "results = pcmci_parcorr.run_pcmci(tau_max=2, pc_alpha=0.2, alpha_level = 0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Masking\n",
    "\n",
    "Different from missing values, masking can be used to include or exclude samples depending on the situation. It is applied by means of the optional parameters ``mask`` and ``mask_type``:\n",
    "- ``mask`` is an optional argument that can be passed when initializing a ``DataFrame`` object. It is a numpy array of the same shape as ``data`` and should contain the values ``0`` (or ``False``) or ``1`` (or ``True``). In this way each entry of ``data`` is associated with a ``0``or a ``1``, where ``0`` means that the entry is *not* supposed to be masked and ``1`` means it is supposed to be masked.\n",
    "- ``mask_type`` is an optional argument that can be passed when initializing a conditional independence test object, for example ``ParCorr``. It is a string that can contain any combination of the characters ``x``, ``y`` and ``z``. If ``mask_type`` is left unspecified as ``None``, then the ``mask`` is not used. ``mask_type`` determines for which type of variables, as determined by their role in a conditional independence test, the mask is supposed to be active.\n",
    "\n",
    "The details are as follows.\n",
    "\n",
    "#### What masking does mechanically:\n",
    "\n",
    "Consider testing whether $X = X^i_{t-\\tau}$ is conditionally independent of $Y = X^j_t$ given $Z = \\{X^k_{t-\\tau_k}, X^l_{t-\\tau_l}, \\ldots\\}$. This particular $Z$ is just for illustration, $Z$ could also be empty or have only one element. The individual samples thus are $s_n = (X^i_{n-\\tau}, X^j_{n}, X^k_{n-\\tau_k}, X^l_{n-\\tau_l}, \\ldots)$ with $2\\cdot\\tau_{\\text{max}} \\leq n \\leq t$ (it is $2\\cdot\\tau_{\\text{max}}$ and not $2\\cdot\\tau_{\\text{max}}$ since the MCI test also conditions on the parents of the lagged variable). Then, the masking functionality excludes the sample $s_n$ from this test if at least one of these three conditions is true:\n",
    "- The value $X^i_{n-\\tau}$ is marked as masked by ``mask`` and the character ``x`` is in ``mask_type``.\n",
    "- The value $X^j_{n}$ is marked as masked by ``mask`` and the character ``y`` is in ``mask_type``.\n",
    "- The value $X^k_{n-\\tau_k}$ or the value $X^l_{n-\\tau_l}$ or $\\ldots$ is marked as masked by ``mask`` and the character ``z`` is in ``mask_type``.\n",
    "\n",
    "Intuitively, a sample $s_n$ is excluded from a conditional independence test if $i)$ one of its entries is a value that is marked as masked by ``mask`` **and** $ii)$ this entries corresponds to the $X$-type (or the $Y$-type or a $Z$-type) variable and ``mask_type`` indicates that the masking should be active for $X$-type (or $Y$-type or $Z$-type) variables.\n",
    "\n",
    "#### Example 1:\n",
    "Say we mark all values $X^i_s$ with $s$ **not** within the time range $[t_0, t_1]$ as masked and choose ``mask_type = y``. Then, only those samples for which the entry corresponding to the $Y$-type variable is taken from a time step within $[t_0, t_1]$ remain. In the above notation, only those $s_n$ with $t_0 \\leq n \\leq t_1$ remain. Note, however, that for some of these remaining samples the entries corresponding to the $X$-type or $Z$-type variables may be taken from outside the time window $[t_0, t_1]$. For example, if $X = X^i_{t-1}$ the sample $s_{t_0} = (X^i_{t_0-1}, X^j_{t_0}, X^k_{t_0-\\tau_k}, X^l_{t_0-\\tau_l}, \\ldots)$ is retained although the value $X^i_{t_0-1}$ involves a time index that is outside the range $[t_0, t_1]$.\n",
    "\n",
    "This is essentially the case that is described in [Kretschmer et al., 2016], with the difference that there the single interval $[t_0, t_1]$ is replaced by several intervals, each of which corresponds to December - February of one year.\n",
    "\n",
    "[Kretschmer et al., 2016] Kretschmer, M., Coumou, D., Donges, J. F., and Runge, J. (01 Jun. 2016). Using causal effect networks to analyze different arctic drivers of midlatitude winter circulation. *Journal of Climate*, 29(11):4069 – 4081. [https://doi.org/10.1175/JCLI-D-15-0654.1](https://doi.org/10.1175/JCLI-D-15-0654.1).\n",
    "\n",
    "#### Example 2:\n",
    "With the same mask as in Example 1, choose ``mask_type = xy``. Then, all samples that were disregarded in Example 1 are also disregarded here. In addition, also the samples $s_n$ with $t_0 \\leq n \\leq t_0 + \\tau - 1$ are disregarded. So if $\\tau = 0$, no further sample is disregarded. If $\\tau = 1$, the single sample $s_{t_0}$ is further disregarded. If $\\tau = 2$, the two samples $s_{t_0}$ and $s_{t_0 + 1}$ are further disregarded. And so on. This indicates that including ``x`` and, yet more so, including ``z`` in ``mask_type`` strongly reduces the number of remaining samples if $\\tau_{\\text{max}}$ is chosen large.\n",
    "\n",
    "To illustrate this, let us look at page 4073 last paragraph to page 4074 first paragraph in [Kretschmer et al., 2016] and see what would have happened if ``mask_type`` had been ``xy`` instead of ``y``. Here, $Y = \\text{PoV}_t$ and $Z$ is empty. For $\\tau = 1$, $X = \\text{EA-snow}_{t-1}$. If ``mask_type`` was ``xy``, also $\\text{EA-snow}$ would be limited to Dec - Feb. Therefore, each year would contribute only 2 instead of 3 samples (for monthly time resolution). These two samples are: $(\\text{PoV in Feb}, \\text{EA-snow in Jan})$, $(\\text{PoV in Jan}, \\text{EA-snow in Dec})$. For $\\tau = 3$, $X = \\text{EA-snow}_{t-3}$ and no samples would be left because $\\text{PoV}$ in Feb would need to be paired with $\\text{EA-snow}$ in Nov, which is out of the non-masked interval Dec - Feb. Similarly, $\\text{PoV}$ in Jan (Dec) would need to be paired with $\\text{EA-snow}$ in Oct (Sept), both of which are out of the non-masked interval.\n",
    "\n",
    "#### What masking can be used for:\n",
    "It allows to make use of background knowledge about causal stationarity, in particular it allows to specify a time range within which a certain causal mechanism is believed to be stationary. This is illustrated in the below figure: Running PCMCI on the whole time series (i.e., without masking) implicitly makes the assumption that the underlying causal structure remains the same over the entire time series, see the figure's upper part. A user may, however, have the background knowledge (or strong believe) that the causal structure may vary over time, for example between two regimes that alternate every 6 months as shown in the figure's lower part (the figure refers to these two regimes as *winter* and *summer* for illustration). In such a case masking allows to separately analyze the different regimes."
   ]
  },
  {
   "attachments": {
    "causal_stationarity_2.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![figures/causal_stationarity_2.png](attachment:causal_stationarity_2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example is similar to the application in [Kretschmer et al., 2016]. There, the use of the ``mask_type = y`` resulted in PCMCI only searching for causal drivers of target variables with the target variables restricted to Dec - Feb. The potential causal drivers, however, were allowed to be not only Dec - Feb. If in this example ``mask_type`` had been ``xy``, then also the potential causal drivers would have been restricted to Dec - Feb. If ``mask_type`` had been ``xyz``, in addition to the target variables and the potential causal drivers also the conditioning variables would have been restricted to Dec - Feb.\n",
    "\n",
    "#### Example 3 (with code):\n",
    "Below we generate data in which the underlying causal structure alternates between two regimes that are referred to as winter half year and summer half year. In particular, the two regimes differ in that one causal effect is of opposite sign in the two regimes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Masking demo: We consider time series where the one part is generated by a different\n",
    "# causal process than the other part. \n",
    "np.random.seed(42)\n",
    "T = 1000\n",
    "data = np.random.randn(T, 2)\n",
    "data_mask = np.zeros(data.shape)\n",
    "for t in range(1, T):\n",
    "#     print t % 365\n",
    "    if (t % 365) < 3*30 or (t % 365) > 8*30: \n",
    "        # Winter half year\n",
    "        data[t, 0] +=  0.4*data[t-1, 0]\n",
    "        data[t, 1] +=  0.3*data[t-1, 1] + 0.9*data[t-1, 0]\n",
    "    else:\n",
    "        # Summer half year\n",
    "        data_mask[[t, t-1]] = True\n",
    "        data[t, 0] +=  0.4*data[t-1, 0]\n",
    "        data[t, 1] +=  0.3*data[t-1, 1] - 0.9*data[t-1, 0]\n",
    "\n",
    "T, N = data.shape\n",
    "# print data_mask[:100, 0]\n",
    "dataframe = pp.DataFrame(data, mask=data_mask)\n",
    "tp.plot_timeseries(dataframe, figsize=(8,3), grey_masked_samples='data'); plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup analysis\n",
    "def run_and_plot(cond_ind_test, fig_ax, aspect=20):\n",
    "    pcmci = PCMCI(dataframe=dataframe, cond_ind_test=cond_ind_test)\n",
    "    results = pcmci.run_pcmci(tau_max=2, pc_alpha=0.2, alpha_level=0.01)\n",
    "    tp.plot_graph(fig_ax = fig_ax,  val_matrix=results['val_matrix'],\n",
    "                  graph=results['graph'], var_names=var_names,\n",
    "                  node_aspect=aspect, node_size=0.02\n",
    "    ); plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPwAAADaCAYAAACCXi9MAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAeiElEQVR4nO2de3QUVZ7Hv7equjshLwjhYUJ4mfAygBoQeQ2yrvIS0VFGZUCQGV2OjKuCy+zsMIPL6pnBWUf0rLrjKIgzDuxRUJkZUZwoSpDBBw9hDBKUgECCkCd5dlfV3T86aQh5dXfqVt1O/T7n5CRd1fW7v9S937q/+yzGOecgCMIVKE47QBCEfZDgCcJFkOAJwkWQ4AnCRZDgCcJFkOAJwkWQ4AnCRZDgCcJFkOAJwkWQ4AnCRZDgCcJFkOAJwkWQ4AnCRZDgCcJFaE47cDGcm9BPfQP9ZCG4qUPt3hverNFg3jinXSOIDuGcwywvgXGqEND9YAkp0PqPAItLcNq1EEyW9fD6d9+iNm8TzPPlAFMABsA0AVVDXO718I3+HhhjTrtJEK1iVpejYfdb4BXfBcsvAHAOMEC9/Cp4R08FU1RnnYQkgvcf2YvaD7cA4MGb1ArawBFI+Kc7wDSPvc4RRAcYZ4rQ8PEbgKG3WX6V1Mvgm3Q7mC/eZu8u8cPR1AEETnyF2h2vA9xs82YBgH68ALU734AEzyeCCGFWfIeG/C2AHmi3/JrlJWj4eAu4adjoXUscFbxRcRY1f9uIYPzeAZwjULgfDV/kC/eLIMKBN9SifufrAA9DxJzDPHcK/n1/E+9YOzgmeM45aj/aEgyDEH6tXf/JuzAqS8U5RhBh4v/iQ6Chpt2a/VKMbw7A+O6EQK/axzHBB44dglFyPBjKR0jd7r8K8IggwscoK4ZRdDAisQMAGIN/33vgZuTl3gocETzXA6j7+C8IK5RvcbEJ/cRhBE4WWu4XQYQD5xyBfX8Dohk14hy8qhT6sQPWOxYGjgi+4cBH4LXnEUko3wzGULdrq+MdIIQ7MU58CbOsOPLa/SICBz8C99dZ6FV42C54rgdQ39mON85hVpYicLzAGqcIIkw45wgU7O68oYAf+rEvOm8nQmwXfOB4ARBo6LwhxuA//Fnn7RBEBJjlJeDnyyywxKF/84Xtw8y2C95/+LPo2j6Xwjn0k4Uwa8933hZBhIlRdMia8guAV5cHmwY2YqvgzZpK6Ke+7lTbpxkc8Bfut8YWQXQAN3Tox/9hXfllSvABYiO2Ct5/ZF9UHfNtw+E//CnNviNswTh9FND91hnkJvQT/wA3AtbZ7ADbBM95UJyWPR0bMSvPwTh7ylKbBNEa+rEvLAvnLxgNwDh11Fqb7WCb4I0zJ4Ir4ayGKfAf+dx6uwRxEWbdeZhniiyvsABma2+9bYL3H9l7YdmglXAT/sJ94IZuvW2CaMQ4/iUsbo82wmF+dxxmnT2dz7YInnMeHI6LYhptWAT80M84Nz+Z6PoYp48i6oliYWCWHBNm+2JsEbxZcRa8rlpcAkyBftK+dhDhLrjuh1l2WlwCjMEoKRJn/yJsEbx+6ijEhEONcBOBk0fE2SdcjXn2WwFt94vgHMaZY7aMNtki+MDJQqF6BwDzXDHMBvvnJhNdH+NMkZj+p4sJNAS3xxKMcMFz04B++huxT8hgStBPfy04DcKNGCXHxPU/hWAwvisSnIYNgjdKS4Lb/4iGKTCKj4tPh3AV3F9n0dz5jjHOfis8DfGCLymC8HgeCLbji78Rnw7hKsxzdk3q4jDPnhTejhcu+EBJkS16BwCzrATcipV4BNGIce6U+PZ7E7of/LzY7duE/ieccxinj9nQfg8lCP2M+LCIcA/m2RM2tN8vYJw9KdS+UMGb58vBG2pFJtEcpsA4Q+14whq4ocMsP2NfgkyBWSq2CSFU8EZZiUjzrcCh254m0VXh1eW21u7gpvAHjNgavuyM9auL2oNzmKX2bihAdF3MynO2p8mry8EFPmTE1vB2hkONmOfLaSENYQlm1Tn7OuxCiRrg1RXCzIsVfGnndvaMCs4deTITXQ+z8pz95ReAWSWup16Y4LlpCHW8PYwy+yMLouvBK7+DyBVyrcIYeJW4CkuY4M2qsuDrnu2GKTDKxc9JJro23NDBayodSVtkhCpM8E603wEEVx45lTbRZbBrOm3LhDlMgYtoxNXw5d/Z3+EBAODBvgOC6ASmwLC6I3h1ubB3zwms4R1o/zTCz1dQTz3RKcyqUocqLADcBK+pEGJanOCd6KEPwWFWnHUobaIrYFaedbD8ioswhAiemwZMh9/hTh13RGcIbkbhkOAZAxfUcSdE8GZNlb1TEi+FKY4NCRKxD+cc3KZdZNvCjKWQntdUiTAbPqzxoUMQ0dBQ42g4D84bX6duPWJq+FqHxWaazvtAxCxCd1gO1wdB5VdcSG/nopnWfDhf4Wj6ROxiyiD4ejE+iAvpHRa8480KImZxuv0OANAD4AL2ghRUw1c62wYCwBtqwU3DUR+I2ITXVTs3Bt/MD+sfPGIEX+284AGA1zofmhGxhwxteEBMWC+uhpcA6rgjooHXnXd2WDnkRwwIngscUogUWR48RGwhRf8PY7ER0nN/PSBF25mB18jx4CFiC1E95JHBYqSGl+HpCAAKo5CeiBhuBADd77Qbwck3sSB4aUTGOc22IyJGlg47gAuZfGO94GURGefB0QKCiAB5BA8hfWFi2vAOT7ppwtaXYBBdApleVcZ1632xflgu0ADbXibXATJlHhEjyNB+b8LQLX+5pPU1fMAvi94bHz4EET48IJHgObd8xEuA4OURmYi5yEQXR/dL0yQFYHnEIaAN3yDFtFoAwQUIsvhCxARc90OeENX6iENMDS+TyGRqkxHyI1t5kb+Gr7faZKeQqYlByI9UbXg0RRzW0fUF75crAwnJ0f1dOkIVNCwnD1TDE5EQrOHlEXwMtOHlqlFJ8EREyFZeZK/hZRO8dBlISI1cFQSTuw3POQckG/uWKwMJ6ZGpl54xQOqQ3ghApvYP0DgvgCDCxOoatbPIXcPr4l7gOP/5zRj48FNY+Lst4V/EGL1UkogMQ8zmLds+L8CVD/4Go/71Cbyc90kE/lhbfi1uw4ur3f/ln8bg+UU3RX6hTEMsRAxgfXnRDQP//spf8Paq+7BrzYP47Vs7UFbtzEpOawUv6J3WADB56AAkxXmjuJIET0SAgOLy2dFvMbxfH6SnpiAp3ocbrxqGv+0/EqY/1mrK0RreNDmu+eXvsGrzB82O5/3jG/S+fw3e/Lygk/4wquGJCAm/vJimiase+m+s/OPbzY6/t/8rdL/rP7Bl9xcAgOLyKqSnJofOZ/RMwemyMDdnkXp5bITOKQrDwzPGY/1He1FRUwcAOPjtGdzzwhv4xS3X4Zbc4bb7RLicCMqLoihYfstUvPje31HeGKJ/UXQaC556FY/eNQ3fHz+qTZMszBV5cq+Hj8K5udfkIDWxG373/mc4VV6FO//nNfxgXA4euHGcYz4Rbiay8nLn5CvRMykBz2/bhVOlFbjt1+tx1+Sr8dDNU0LfSU9NxumyC1u/nSqtRN8eSWH6Ym351Sy1FoW4NFXBg9OuxX+9uQNb932FUf37YM2dNzjqE+FiIiwumqpi2ZwpeHTju3hzzyFcOSgD/7345mbfGZOViS+/LcHpskokxcdh+77D+Nnt1wvxpyOsHZaL8rq511yBOr8OzoEXfzwHqtLSrdue3oRFL7yB9w5+jSt++j/YW3S6Y8OsM14R7iTy8nLH5KtQ2+AH58DLD85rUX41VcWv7r4JM/7zBUxY8TQeunkKeiYlhOmOxDV8uO2SS1mxaTsAoKy6tlWxA8DmB++M3DCHFC8FJGIIFnlH77KX3gIAlJ6vgaq0roFZY0Zg1pgR0fljIdaqIQrnHn/rQ2w/eBTbf3o3dNPEH/IPWOqSVNsVETFAZOVl9aZ38e7ew/jg8aUwDBMb3v/UWl+6kuBfyd+PZ9/7BBuXzsXIzD5Ycv1YPLP97whYOtuJBE9EQARl+OW8T/DMX3bitZ8uxKiB6Vg6axKe2vohArp15TfaqLktLI53w3fuvUNf4982bsfvFt+MsYMzAAD3TR2D8/V+/N/fD1nkD6canhDCu/sO4+GX3sRLD9yJa4YMAAAsmT4B5+sa8KeP9lqXkNSCD9O5/ceLcc8Lb+A/vz8Vs68eGjqeHO/DfVNzsfad3TCsmrVHgiciIYzysu+bk1jw21fx2PyZmDMuJ3Q8uVsclkyfgN++tcO68mtxhMq4hSP7Zn0tql55zCpznYcxxF07E3EjJzrtCREj1G55qnHVpwQwBdrlV8J71T9bZtLSGp6pqpXmOg/n8vlEyE0bo0SOoVhbfq397zSPpeasgHl8TrtAxBBMi2aBljis9sfaGp4pgCqZ6EnwRCRIJXgOeCQWPAAwj1yCZxbfMKJrI1V54VzuGh6AdDUqhfRERMhWXmQXvGwCk80fQm6C5UWeoVyrIw7rBe+Ns9pkpyDBExGheeWauyF9De+VS2Cy+UPIjVRteADM4pEvMSF9F35CEl0c2cqL9DW8TIJXNTDZJlIQUhPsFZdnD4UYaMPL0+lhdThEuACPV65dkmKihpflCUkddkSEyDbTzuqJbGLG4SV5QsrWAUPEADIJXvXIvh6+MaSXRfCSDRES8iNVJSGgSWq54JX4cLbftQHGoCSkOO0FEWOwuESnXQghwhfra/iE5I6/ZAckeCIKWLxEghegJetreFkEz7k8Dx8iZmAeH6Ba+7qG6BxRhETL1tfwcd3k2BqacyjdJGleEDEF84W5Z7xgREQb1gueKWDxctwwaaINIqZgMlQU3IwNwQOQpu3MJPGDiC1Yt2QpZouyWAjpAUBJ7A4ZZttRSE9EQ1BozpffmKnhWUIS0MYrd2zD46OptURUsPhEgFu1zXQn/IiFYTkAULqlOD75hmp3IlqkGJpTVCFTwwW14ZOdF3xSD0fTJ2IXEW3niH2IS7B8Wi0gMqR3EqZQDz0RNTLU8KJGCsSF9E7CJJrxR8QcLM7pYWUWHCkQgKBeeocFb5pQEimkJ6KDKSrg6+agAwxMUKUpJqTXPGAOi17t0dvR9InYRknp5Vzi3ISS3FOIaWFzYNXUy+DkWCYJnugMSkovR6eIKylpYuwKsQpATe3j2GwlFp9Ia+GJTqGkpDk6Fs+SYq2G79HHsRum9uzrSLpE14Eli6lhw0q7WzKYoBV7wgSvOBVSKwrUVBI80TlEtaE7hoF1F6cdcTV8915wpA1vmlB69LE/XaJLwTw+wInhOcaEdhgKE7yTPfXUYUdYgSM99QJ76AGBggcAtaczPfUkeMIKnOqpVwT2H4gVvAM99axbEr1AkrAEJdmJnnoGlpQqzLpYwTvQUx+MKgii8zBBY+HtppkgroceEC54m0NrpgQfMgRhAYrAmrZ1xPbQA4IFr/ToLWQz/TbhJtQ+/e1Lj+jSMI9PaHjdGmrPDKH2hQqeKSo0mwWo9R1ga3pE10bt3d/GjjsOJa2f0BSE/yfaZYNs67hTklKhSLCWmeg6KGn97OuHUlThc0iEC17tO9Ce3W8UBVr6YPHpEK5CdI3bLK3Uy4JLc0WmIdQ6AK13pj0hkWlCpXCesBilWzJgx/vmGIPSK1N4MsKVyDQP1N7i/xEA8GRcbks6hLtQ+w4SX2lxDrW3+ArLlt4IT2a28Ha8kpTauB8+QViL2meA+Ha8okLpmS42DdgkeC0jS2w7XlGgZQ4RZ59wNeJr3mA4L3LCTRO2CF7tlQFoXnEJmCY8/bLE2SdcDYtLABO8XFbtO0io/SZsETxTVGgiw3pGPfSEWNTLsgQ2SznUPl1I8ADgy75KTFjPFGgDh9OWVoRQtAEjhDVLWUovYXvYXYptgtf6DwXzxVtvmJvwDc213i5BXISS0gssRcw8d23QKCF2W8M2wTNFhXfI1ZYPb7C4BGj9si21SRCtoQ0WIEzGoPUfbr3dNrB1db93yNXWDm8wBd6hucJnJxEEgKAwraywmAIlPQvMxpde2Cp4tedlUKzcYJKbwYcIQdgA88ZDzbCw846b8AwcaY2tMLF9/x7fsLEWWWJQ0zJoOyvCVrSBo6zrvPPGQ+lr7+iS7YL3ZI22KCzi8A4bY4Edgggfpe9Aa947xxi0QSPBFHslaLvglbhu8GRf2WnRM28cvFmjrXGKIMKEMQWebGtGhbTB9pdfR16eFX/NNEDtXEdb3LjpNPZOOII2ZAxYfBKi35GZQRsy1pE3HDsieKVbEuJyr4/uYsag9OgD71AK5wlnYKoHniuvBxBlW94bB8/w8Zb6FC6OvR7TlzMh+ISLtMeTc3SbdLPtbR+CuBg1Izu4OUYUPfbe0dc5tpW6Y6phqob4790aYY8ng2fI1cFtswjCQRhj8ObeGFlfFGNQ0jKgDsgR51gHOFpNevplIe7aGeF9mSlQ09LRbdIcsU4RRJgoyWnwjpsd3pcZA4tLhG/CrWAOvUYdcFjwAOAbOQneEde2/yXGoCT1QML0BWB2bntNEB2g9RsCz+ip7X+JMcATB9/k222dVdeqK5zbscNkxzQUfIK6/K0A+IUwnykAN6ENGI6EqXOpV56QFv30Ufj//mfACFw4yBjAOZTUy+CdcAuU+CTnHGxySRbBA4BZUwX/V58j8O1XgKFDSe0L37CxUPv0dzQMIohw4P566Mf/AePUEfBAA5TEHtAGjYTSZyCYAy+lbA2pBE8QhFjkeOwQBGELJHiCcBEkeIJwESR4gnARJHiCcBHCdr6PG7sEqi8equaF6o2D6ouH5o2HonmheuMbP3ugqgo0jwrNq0LzKFC0xs+e4G9VUxDvVdHNqyLeq8GrKYj3NH1Wg5+9KuI0FXGaAo/C4NMU+C75HPxbgaYCKmPwKAyawuBRADX0N4PCDTBTBzMCgOEH0/2AaYA1/s2MAGDq4P568Ib64G/df+Fvfz14wA/ur4dR7w/+BAIw6v3Q65o+6zDqG6DX+6HXBWAETOh1OvR6HXqdDiNgQK/TEWj6rJuoM0zUGRx1Boff5KgzTNQ3/g5+5vhfXiQqO+HLvReqNx6aLx6K5rkoDxvz1BcPzeuD5lGb56FXDeajqkDzBo835VtTnsZ7VPga87Hpx6sqwXxr/O1RFfjUYD76GvPSq13IR5Uh+LcaPKYyQFMYNAYwo3kewgg05rEf0ANghh9cD4A31F2Uh4ELfzfUAXoARkNDMB/rG2D6deiN+avX+2EGAo35G0CgXofpN0L5p9frMPxGKH8DDUYoD9vL02dN6/OTaniCcBEkeIJwESR4gnARJHiCcBEkeIJwESR4gnARJHiCcBEkeIJwESR4gnARJHiCcBPcIerr6/mqVat4fX29NLa6uk8i6er3TlZbkeLYjjdVVVVISUlBZWUlkpOTpbDV1X0SSVe/d7LaihQK6QnCRZDgCcJFkOAJwkU49245nw+rVq2Cz9f5d2xZZaur+ySSrn7vZLUVKbRNNUG4CArpCcJFkOAJwkWQ4AnCRZDgCcJFOCL4Rx55BJMnT8YPf/hD+P3+Zufq6upw0003YcqUKbjhhhtQVlYWlZ0mfvWrX2HMmDERXa/rOhYtWoTJkyfjwQcf7PT/1JEf4diJ5L7YjVX52ZGtJtq6lzLmZ3u2nMhT2wW/b98+lJSUYOfOnRgxYgRef/31Zue3bduGnJwcfPjhh/jBD36AP/zhD1HZAYDz58/j0KFDEV//5z//Gf369cPOnTtRW1uLjz/+uFP/U3t+hGsn3PtiN1blZzi2gLbvpYz52ZEtJ/LUdsHv3r0bN954IwBg+vTpLW5+dnY2amtrAQAVFRXo1atXVHYA4Omnn8bSpUsjvj4c25H40p4f4doJ977YjVX5GY4toO17KWN+dmTLiTwV9iKKtqioqEB6ejoAICUlpUUYc/nll+PQoUPIyckBYwx79uyJyk5lZSUOHjyIlStXRnx9RUVFaFFDa7YjsdWRH+HaCfe+2I1V+RmOrfbupYz52ZEtJ/JUmOBLSkpw++23tzg+Y8YMVFVVAQjejNTU1GbnN2zYgOuuuw6//OUvsWXLFqxYsQL79++P2M7atWvxk5/8pE3/evTo0eb17Z2L1FZHfoRr59L7snr1avz6178Oy64VWJWfq1evxkMPPRSVrfbupYz52ZEtJ/JUWEjft29f5Ofnt/iZOXMmtm/fDgB49913MXHixBbXNt2U7t27Q9f1qOwcPXoUjz/+OKZPn47CwsIWN/Laa69t8/r2zrVGe9/vyI9w7Vx6XyoqKtr1yWqsys+KioqobbV3L2XMz3DStj1PbV+Bzzlfvnw5nzRpEp83bx5vaGjgnHN+3333cc45r6ys5DNnzuRTpkzhEydO5F999VVUdi4mNzc3rOubrg0EAvzuu+/mkyZN4g888EBU/1MkfoRjJ5L7YjdW5WdHti6mtXspY362Z8uJPKW59AThImjiDUG4CBI8QbgIEjxBuIguLfiXX34Z3bt3t8RWUVERGGPQNA2nTp1qdq64uBiapoExhqKiombnNm/ejOuuuw4pKSlITEzEqFGjsHr16tB4rJU+uoVFixaBMYYlS5a0OHf//feDMYZFixaFjpWUlOCBBx7A4MGD4fP5kJmZidmzZyMvLy/0nYEDB2Lt2rU2eO8sXVrwIkhPT8crr7zS7NiGDRuQkZHR4rs///nPcccdd2Ds2LHYtm0bDh06hCeffBIHDhyQZmpsrJKZmYlNmzahrq4udKy+vh4bN25E//79Q8eKioqQm5uL999/H0888QQOHjyId955B1OnTg17tlyXQvg4QCfYtm0bnzhxIk9JSeGpqal81qxZ/OjRo5xzzj/44AMOgJeXl4e+v2/fPg6AHzt2LHT+4p9Vq1ZxzjkvKyvjCxYs4N27d+fx8fF8+vTp/MiRI+36cuzYMQ6Ar1y5kmdnZzc7N3ToUP6LX/wilDbnnO/Zs4cD4GvXrm3VXpPf69ev5ykpKRHfGzezcOFCPmfOHD5y5Ej+xz/+MXT81Vdf5SNHjuRz5szhCxcu5JxzPmPGDJ6RkcGrq6tb2Lm47AwYMIA/9dRTgj13Hqlr+JqaGixbtgyffvop8vLyoCgKbr31Vpim2eG1EyZMwNq1a5GcnIzi4mIUFxfjkUceARAMCT/77DNs3boVu3fvBuccM2fORCAQ6NDuzTffjPLycuTn5wMA8vPzUVZWhtmzZzf73quvvorExETcf//9rdqhML7z3HPPPVi/fn3o87p167B48eLQ57KyMrzzzjtYunQpEhISWlzvxjywfS59JNx2223NPr/00kvo3bs3vvzyyw6v9Xq9SElJAWMMffv2DR0vLCzE1q1bsWvXLkyYMAFAUJyZmZl48803MXfu3HbtejwezJ8/H+vWrcOkSZOwbt06zJ8/Hx6Pp9n3CgsLMXjw4BbHCetYsGABfvazn4X6V3bt2oVNmzZhx44dAIKz4jjnGDZsmLOOSoTUNfzXX3+NefPmYfDgwUhOTsagQYMAACdOnIjaZkFBATRNw7hx40LHevbsiaFDh6KgoABAcE53YmIiEhMTccUVV7Sw8aMf/QivvfYaSkpK8NprrzWrVZrgnIMxFrWfRMekpaVh1qxZ2LBhA9avX49Zs2YhLS0tdJ43zimjfLiA1DX87NmzkZmZid///vdIT0+HaZrIycmB3+9HYmIigAuZCiCskJy3MbHwYoG++OKLoc6g1mronJwcDBs2DHfddReGDx+OnJycFgt8hgwZgvz8fAQCAarlBbJ48eLQYpZnn3222bns7GwwxlBQUIBbbrnFAe/kQ9oavrS0FAUFBVi5ciWuv/56DB8+HOXl5aHzTWuHi4uLQ8cuFZ3X64VhGM2OjRgxArquN1uKWFpaiiNHjmD48OEAgIyMDGRlZSErKwsDBgxo1b/Fixdjx44drdbuADBv3jxUV1fjueeea/W83YtfuirTp0+H3++H3+/HtGnTmp1LTU3FtGnT8Oyzz6KmpqbFtW7MA2kF36NHD/Ts2RMvvPACjh49ivfffx/Lli0Lnc/KykJmZiYeffRRHDlyBH/961/x5JNPNrMxcOBAVFdXIy8vD+fOnUNtbS2ys7MxZ84c3HvvvcjPz8eBAwcwf/58ZGRkYM6cOWH7d++99+Ls2bP48Y9/3Or5cePGYcWKFVi+fDlWrFiB3bt34/jx48jLy8PcuXOxYcOG6G4M0QxVVVFQUICCggKoqtri/HPPPQfDMHDNNddg8+bNKCwsREFBAZ555hmMHz/eAY+dRVrBK4qCTZs24fPPP0dOTg4efvhh/OY3vwmd93g82LhxIw4fPozRo0djzZo1eOyxx5rZmDBhApYsWYI77rgDvXr1whNPPAEAWL9+PXJzc3HTTTdh/Pjx4Jzj7bffjij01jQNaWlp0LS2W0Vr1qzBn/70J+zZswfTpk3DFVdcgWXLlmHUqFFYuHBhhHeEaIvk5OQ238I6aNAg7N27F1OnTsXy5cuRk5ODG264AXl5eXj++edt9tR5aLUcQbgIaWt4giCshwRPEC6CBE8QLoIETxAuggRPEC6CBE8QLoIETxAuggRPEC6CBE8QLoIETxAuggRPEC7i/wEh+Jlj9+jwQAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 300x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Causal graph of whole year yields no link because effects average out\n",
    "fig  = plt.figure(figsize=(3,2)); ax=fig.add_subplot(111)\n",
    "run_and_plot(ParCorr(mask_type=None), (fig, ax))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Causal graph of winter half only gives positive link\n",
    "fig  = plt.figure(figsize=(3,2)); ax=fig.add_subplot(111)\n",
    "run_and_plot(ParCorr(mask_type='y'), (fig, ax))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Causal graph of summer half only gives negative link\n",
    "fig  = plt.figure(figsize=(3,2)); ax=fig.add_subplot(111)\n",
    "dataframe.mask[0] = (dataframe.mask[0] == False)\n",
    "run_and_plot(ParCorr(mask_type='y'),  (fig, ax))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note, however, that the failure to detect the link on the whole sample occurs only for partial correlation because the positive and negative dependencies cancel out. As shown below, using CMIknn recovers the link. To make CMIknn faster, here we use the option ``significance='fixed_thres'``, then ``pc_alpha`` and ``alpha_level`` are interpreted as a threshold $I^*$ in any conditional independence test. See the tutorial on conditional independence tests for further details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "cmi_knn = CMIknn(significance='fixed_thres', mask_type=None)\n",
    "\n",
    "fixed_thres = 0.01\n",
    "pcmci = PCMCI(dataframe=dataframe, cond_ind_test=cmi_knn)\n",
    "results = pcmci.run_pcmci(tau_max=2, pc_alpha=fixed_thres, alpha_level=fixed_thres)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_ax = tp.plot_graph(val_matrix=results['val_matrix'],\n",
    "              node_aspect=20,\n",
    "              node_size=0.02,\n",
    "              figsize=(3,2),\n",
    "              vmin_edges=0.,\n",
    "              vmax_edges = 0.1,\n",
    "              edge_ticks=0.05,\n",
    "              cmap_edges='OrRd',\n",
    "              vmin_nodes=0.,\n",
    "              vmax_nodes= 0.1,\n",
    "              node_ticks=0.05,\n",
    "              cmap_nodes='OrRd',\n",
    "              graph=results['graph'], var_names=var_names)\n",
    "fig_ax[0].tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tigenv",
   "language": "python",
   "name": "tigenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
